Feature Extraction
Transformers
PyTorch
English
modernbert
fill-mask
encoder
text-embeddings-inference
Instructions to use jhu-clsp/ettin-encoder-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jhu-clsp/ettin-encoder-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jhu-clsp/ettin-encoder-1b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jhu-clsp/ettin-encoder-1b") model = AutoModelForMaskedLM.from_pretrained("jhu-clsp/ettin-encoder-1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jhu-clsp/ettin-encoder-1b: direct link, hf CLI and curl.
- Browser
- Download file 4.13 GB
-
https://huggingface.co/jhu-clsp/ettin-encoder-1b/resolve/187ee663f85ed0f82dff4910511ee87eef79edae/pytorch_model.bin
- Command line
-
hf download hf://jhu-clsp/ettin-encoder-1b@187ee663f85ed0f82dff4910511ee87eef79edae/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jhu-clsp/ettin-encoder-1b/resolve/187ee663f85ed0f82dff4910511ee87eef79edae/pytorch_model.bin
4.13 GB
- Xet hash:
- a9515bcec3a200b02d6cf6560a434af51536dd213388161f71d9cd36deb6d716
- Size of remote file:
- 4.13 GB
- SHA256:
- b4630d7255b98e8176e9b19300786d3ab30534beae8c629f2a1a8829ec85875e
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